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Enhanced Model-Based Clustering, Density Estimation, and Discriminant Analysis Software: MCLUST

Citations

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Cited by:

  1. Crowley, Patrick M., 2008. "One money, several cycles? : evaluation of European business cycles using model-based cluster analysis," Research Discussion Papers 3/2008, Bank of Finland.
  2. repec:zbw:bofrdp:2008_003 is not listed on IDEAS
  3. Rossell David & Guerra Rudy & Scott Clayton, 2008. "Semi-Parametric Differential Expression Analysis via Partial Mixture Estimation," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-29, April.
  4. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
  5. repec:jss:jstsof:14:i12 is not listed on IDEAS
  6. Lin, Tsung-I, 2014. "Learning from incomplete data via parameterized t mixture models through eigenvalue decomposition," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 183-195.
  7. Wentao Fan & Nizar Bouguila, 2013. "Infinite Dirichlet mixture models learning via expectation propagation," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 7(4), pages 465-489, December.
  8. Warren C Jochem & Douglas R Leasure & Oliver Pannell & Heather R Chamberlain & Patricia Jones & Andrew J Tatem, 2021. "Classifying settlement types from multi-scale spatial patterns of building footprints," Environment and Planning B, , vol. 48(5), pages 1161-1179, June.
  9. Christian Hennig, 2010. "Methods for merging Gaussian mixture components," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 4(1), pages 3-34, April.
  10. Maugis, C. & Celeux, G. & Martin-Magniette, M.-L., 2011. "Variable selection in model-based discriminant analysis," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1374-1387, November.
  11. Galimberti, Giuliano & Montanari, Angela & Viroli, Cinzia, 2009. "Penalized factor mixture analysis for variable selection in clustered data," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4301-4310, October.
  12. Cathy Maugis & Gilles Celeux & Marie-Laure Martin-Magniette, 2009. "Variable Selection for Clustering with Gaussian Mixture Models," Biometrics, The International Biometric Society, vol. 65(3), pages 701-709, September.
  13. Hornik, Kurt, 2005. "A CLUE for CLUster Ensembles," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i12).
  14. Jeffrey Andrews & Paul McNicholas, 2014. "Variable Selection for Clustering and Classification," Journal of Classification, Springer;The Classification Society, vol. 31(2), pages 136-153, July.
  15. Salter-Townshend, Michael & Murphy, Thomas Brendan, 2013. "Variational Bayesian inference for the Latent Position Cluster Model for network data," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 661-671.
  16. repec:jss:jstsof:18:i06 is not listed on IDEAS
  17. Alex Sharp & Glen Chalatov & Ryan P. Browne, 2023. "A dual subspace parsimonious mixture of matrix normal distributions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(3), pages 801-822, September.
  18. Minin Vladimir N. & O'Brien John D. & Seregin Arseni, 2011. "Imputation Estimators Partially Correct for Model Misspecification," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-24, April.
  19. Cinzia Viroli, 2010. "Dimensionally Reduced Model-Based Clustering Through Mixtures of Factor Mixture Analyzers," Journal of Classification, Springer;The Classification Society, vol. 27(3), pages 363-388, November.
  20. Xun-Heng Wang & Lihua Li & Tao Xu & Zhongxiang Ding, 2015. "Investigating the Temporal Patterns within and between Intrinsic Connectivity Networks under Eyes-Open and Eyes-Closed Resting States: A Dynamical Functional Connectivity Study Based on Phase Synchron," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-20, October.
  21. Andrews, Jeffrey L. & McNicholas, Paul D. & Subedi, Sanjeena, 2011. "Model-based classification via mixtures of multivariate t-distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 520-529, January.
  22. Crowley, Patrick M., 2008. "One money, several cycles? Evaluation of European business cycles using model-based cluster analysis," Bank of Finland Research Discussion Papers 3/2008, Bank of Finland.
  23. Barnes, Andrew P. & Bevan, Kev & Moxey, Andrew & Grierson, Sascha & Toma, Luiza, 2023. "Identifying best practice in Less Favoured Area mixed livestock systems," Agricultural Systems, Elsevier, vol. 208(C).
  24. McNicholas, P.D. & Murphy, T.B. & McDaid, A.F. & Frost, D., 2010. "Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 711-723, March.
  25. Hien D. Nguyen & Geoffrey J. McLachlan & Jeremy F. P. Ullmann & Andrew L. Janke, 2016. "Spatial clustering of time series via mixture of autoregressions models and Markov random fields," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 414-439, November.
  26. Farzaneh Khajouei & Saurabh Sinha, 2018. "An information theoretic treatment of sequence-to-expression modeling," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-24, September.
  27. Mayra Z Rodriguez & Cesar H Comin & Dalcimar Casanova & Odemir M Bruno & Diego R Amancio & Luciano da F Costa & Francisco A Rodrigues, 2019. "Clustering algorithms: A comparative approach," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-34, January.
  28. Shuai Shao & Bifeng Hu & Zhiyi Fu & Jiayu Wang & Ge Lou & Yue Zhou & Bin Jin & Yan Li & Zhou Shi, 2018. "Source Identification and Apportionment of Trace Elements in Soils in the Yangtze River Delta, China," IJERPH, MDPI, vol. 15(6), pages 1-14, June.
  29. Zhang, Ping & Serban, Nicoleta, 2007. "Discovery, visualization and performance analysis of enterprise workflow," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2670-2687, February.
  30. Atkinson, A.C. & Riani, M., 2007. "Exploratory tools for clustering multivariate data," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 272-285, September.
  31. Hennig, Christian, 2008. "Dissolution point and isolation robustness: Robustness criteria for general cluster analysis methods," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1154-1176, July.
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